Users of smartphones and other mobile devices often want to know about their context or surroundings. For example, a user may want to determine their location, whether the immediate environment includes natural or artificial light, or whether a particular device, such as a TV, radio, or microwave is nearby. In addition, smartphone applications can leverage contextual information to provide additional services, or enhanced services, to the user. A smartphone operating system itself can use contextual information to better manage system resources. For example, if the environment around the device is relatively static, then some operations can be delayed, saving precious battery power.
Mobile devices collect optical information through sensors, such as an ALS (ambient light sensor) and a camera, which can include an RGB (red, green, blue) sensor. The ALS sensor senses surrounding light levels and typically adjusts the brightness of a display, e.g., a screen. Thus, an ALS sensor does not provide a user with much information regarding his surroundings. A camera, on the other hand, captures light information to produce an image, but uses a lot of power. Thus, it is not currently practical to have a camera always running to determine the environment of a user.
Accordingly, a need exists for a simple and low power sensor to determine user context.